Data Resampling Technologies Applied to DDoS Attack Detection of IoT Devices with Machine Learning Application

Yang Ye ； Jiaxin Zhao ； Yifan Zhan

《World Scientific Research Journal》 6卷10期 (2020/10) Pp. 350-357

https://doi.org/10.6911/WSRJ.202010_6(10).0042

摘要

With increasing Internet of Things device connected to the Internet, security problems have raised awareness. Distributed denial of service (DDoS) is a kind of common and dangerous attack towards particular Internet infrastructure, which arouses the necessity to develop powerful technologies to detect such attack. Former researches have discussed various detection models. However, due to lack of big data in the real world, some researches built their models using simulative data, which has imbalance between different classes. This project applies data resampling technologies to solve the problem of imbalance and compares the detection ability of some widely used machine learning applications using the balanced data. The results indicate that using balanced data help train models better and machine learning algorithms can detect DDoS attack.

關鍵字

Internet of Things ； DDoS ； data resampling ； machine learning

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